Triple
T35959403
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Great Storm of 1913 |
E1039954
|
entity |
| Predicate | shipwreckCount |
P53939
|
FINISHED |
| Object | over 30 ships sunk or stranded |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: over 30 ships sunk or stranded | Statement: [Great Storm of 1913, shipwreckCount, over 30 ships sunk or stranded]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: shipwreckCount Context triple: [Great Storm of 1913, shipwreckCount, over 30 ships sunk or stranded]
-
A.
numberOfShipwrecks
chosen
Indicates the quantity of shipwrecks associated with a given entity or context.
-
B.
shipwreckEvent
Indicates an event in which a ship is destroyed, stranded, or severely damaged, typically resulting in loss or abandonment at sea or near a shoreline.
-
C.
shipwreck
Indicates that a vessel has been destroyed, stranded, or severely damaged, typically at sea or near a shoreline.
-
D.
shipwreckInvolved
Indicates that an entity was involved in a shipwreck event, either as a participant, cause, or affected object.
-
E.
shipwreckUse
Indicates that an entity makes use of, interacts with, or derives benefit from a shipwreck.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69f76e26b21081909fd9ffb3aff6c77a |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f7ac23d1388190bdf9628b294943bd |
completed | May 3, 2026, 8:12 p.m. |
| PD | Predicate disambiguation | batch_69f7ab734d848190a84f9b8c3a952b75 |
completed | May 3, 2026, 8:09 p.m. |
Created at: May 3, 2026, 4:07 p.m.